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Dan Spielman is a Sterling Professor in the Department of Mathematics at Yale University. His research interests encompass various fields, including Computer Science, Statistics, and Data Science. Spielman has made significant contributions to the development of algorithms, particularly in relation to spectral graph theory and machine learning. He has published numerous papers and led projects that integrate theory with practical applications, bridging the gap between mathematics and computer science. He is recognized for his work in optimization problems and has been instrumental in advancing the fields of data analysis and computational efficiency.
Administered via the Graduate School of Arts and Sciences (GSAS). GRE General is optional for PhD.